1. Field of the Invention
The present invention relates to a method of managing a manufacturing process, and more particularly to a managing method for a semiconductor manufacturing process including a wafer process (WP), a test process (TP) and an assembly process (AP).
The present application claims priority under 35 U.S.C. §119 to Japanese Patent Application No. 2001-122621, filed Apr. 20, 2001, which is herein incorporated by reference in its entirely for all purposes.
2. Description of the Related Art
As a conventional method for controlling a manufacturing process, an administrator, for example manager, assistant manager, or leader, controls various manufacturing parameters, judges conditions of the various manufacturing parameters, and then outputs instructions in accordance with the conditions. A controlling system is established such that a graph and a report in accordance with various process data are automatically outputted through a local area network (LAN).
Specific manufacturing parameters are described below.
1) Work-in-progress (WIP) for every section, when a manufacturing process has a plurality of sections.
2) WIP for every area, when the manufacturing process is divided into a plurality of areas.
3) Speed control for the sections or areas.
4) Performance control of the manufacturing process.
5) Condition research for various troubles and maintenance.
An inventor of this application proposed a managing method and managing system for a semiconductor manufacturing equipment using a Mahalanobis distance, published in 2000, and in Japanese Laid-Open Patent Publication: P2000-114130A, published on Apr. 21, 2000. Commonly assigned U.S. patent application Ser. No. 09/276,804, filed on Mar. 26, 1999, and entitled “METHOD AND SYSTEM FOR MANAGING SEMICONDUCTOR MANUFACTURING EQUIPMENT”, now U.S. Pat. No. 6,438,440, which is incorporated herein by reference in its entirety. The Mahalanobis distance is a representative one of macroscopic multidimensional space analysis (multivariate analysis). Examples of macroscopic multidimensional space analysis include, for example the Mahalanobis distance, a k-Nearest neighbor method, a Beyes decision boundary, a Discriminant analysis, a Ward method, an Euclidean distance, a Chessboard distance, a Furthest neighbor method, a Nearest neighbor method, a Centroid method, and an Average method.
However, in the conventional method for controlling a manufacturing process, since there are too many graphs and reports needing to be controlled, it is very difficult to make a judgement about timing of carrying-in, timing of carrying-out, and a throughput of product. And, it requires many man-hours to make a judgement about them. Since such a judgement fairly depends upon the administrator's know how, a wide difference in judgement occurs corresponding to different administrators.
More further, there are too many manufacturing parameters and they undergo a lot of changes in accordance with an operating condition of a manufacturing apparatus, and the judgement and instruction of the administrator. Therefore, it is very difficult to logically define the impacts on productivity considering the factors mentioned above.
For example, when a plurality of manufacturing apparatus are stopped together, it is very difficult to exactly find out a productivity deterioration considering various factors (priority, urgency, and so on).